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2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2016)
Chicago, IL, USA
May 23, 2016 to May 27, 2016
ISSN: 1530-2075
ISBN: 978-1-5090-2141-3
pp: 1051-1060
In supercomputer centers, available power, cooling, or carbon footprint often limits supercomputer performance. We propose a new approach to continue scaling that avoids many of these limits, augmenting a traditional system with another that employs only "wasted" renewable power, stranded power. This excess power cannot be economically distributed through grid, and is only intermittently available. We call this approach Zero-carbon Cloud (ZCCloud). We explore the potential benefits of unreliable resources with production DOE HPC workloads using a simple periodic model, and identify job types that benefit most (capability jobs and on-time jobs). The benefits scale with duty factor and resource quantity. Next, to create realistic models of "stranded power" we study 28 months of Mid-continent Independent System Operator (MISO) power market history (1,259 generators, 77 million 5-minute intervals). We find that opportunity varies, but the best single wind site can provide 80% duty factor, and 20MW average stranded power. Combining sites further improves duty factor. With resource volatility models from the MISO study, we simulate production DOE HPC workloads and find that stranded power HPC, ZCCloud, can provide significant benefit, decreasing average job-wait time by 50%.
Power grids, MISO, Wind, Supercomputers, Generators, Cooling, Carbon dioxide,Power limits, High-Performance Computing, Cloud, Power Grid, Batch Scheduling
Fan Yang, Andrew A. Chien, "ZCCloud: Exploring Wasted Green Power for High-Performance Computing", 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), vol. 00, no. , pp. 1051-1060, 2016, doi:10.1109/IPDPS.2016.96
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